Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the claims at issue are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); and In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on a nonstatutory double patenting ground provided the reference application or patent either is shown to be commonly owned with this application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
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Claims 1-20 are provisionally rejected on the ground of nonstatutory obviousness-type double patenting as being unpatentable over claims 1-20 of copending U.S. Application No. 18/956,340, published as US 2026/0145643 A1. Although the claims at issue are not identical, they are not patentably distinct because the presently claimed subject matter represents an obvious variation of the collaborative vehicle deterrence system claimed in the copending application.
The claims of copending Application No. 18/956,340 recite a vehicle-based security system configured to obtain sensor data indicative of a potential threat, determine one or more deterrence actions in response to the potential threat, and deploy one or more neighboring vehicles to implement the deterrence actions. The claims further encompass collaboration between the vehicle and the neighboring vehicles in performing the deterrence response.
Present claim 1 similarly recites detecting suspicious activity occurring in an environment, determining a collaborative deterrence strategy for deterring the suspicious activity, assigning sub-tasks of the collaborative deterrence strategy to a group of vehicles based on respective resource and capability profiles of the vehicles, and controlling at least one vehicle of the group of vehicles to perform an assigned sub-task.
The claims of the copending application therefore teach the underlying inventive concept of multiple vehicles collaboratively responding to detected suspicious or threatening activity by causing neighboring vehicles to participate in deterrence actions. The principal difference presented by claim 1 is that the collaborative deterrence actions are expressly divided into sub-tasks and assigned among participating vehicles according to the resources and capabilities available to each vehicle.
It would have been obvious to one of ordinary skills in the art, having the collaborative multi-vehicle deterrence system claimed in Application No. 18/956,340, to assign particular deterrence functions to particular participating vehicles according to the resources and capabilities of those vehicles. A vehicle necessarily must possess the equipment or capability required to perform the particular deterrence function assigned to it. Selecting among collaborating vehicles according to their available capabilities therefore amounts to an obvious implementation of the already-claimed collaborative deployment of neighboring vehicles and does not render the presently claimed subject matter patentably distinct.
Claim Objections
Claims 11 and 20 are objected to because of the following informalities:
Regarding claim 11, it appears the claim should read “responsive to detecting: instead of “responsive detecting”. Appropriate correction is required.
Regarding claim 20, it appears the claim should read “NLP” instead of “NPL”.
Allowable Subject Matter
Claims 8, 11 and 14 objected to as being dependent upon a rejected base claim, but would be allowable if rewritten in independent form including all of the limitations of the base claim and any intervening claims.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
The factual inquiries for establishing a background for determining obviousness under 35 U.S.C. 103 are summarized as follows:
1. Determining the scope and contents of the prior art.
2. Ascertaining the differences between the prior art and the claims at issue.
3. Resolving the level of ordinary skill in the pertinent art.
4. Considering objective evidence present in the application indicating obviousness or nonobviousness.
Claims 1-2, 4, 12, 15, 17 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Björkengren et al. (US 2020/0108796 A1, hereinafter “Volvo”) in view of Cui et al. (US 2022/0171385 A1).
Regarding claim 1, Volvo teaches detecting suspicious activity being perpetrated by one or more individuals in relation to vehicles. Volvo teaches monitoring the surroundings of vehicles using vehicle sensors and detecting conditions indicative of a security breach, including glass breakage, screams, intrusion, physical attack, and other potential security-related events. Volvo further teaches determining a likelihood of a security breach using information obtained from multiple vehicles. (Volvo, paras 0040-0046, 0056, 0060-0061, 0074, 0078-0082).
Volvo further teaches responsive to detecting the suspicious activity, determining a collaborative strategy to deter the suspicious activity. In particular, when a security breach is detected, Volvo teaches triggering alarms associated with multiple vehicles in a vehicle network. Volvo teaches that a vehicle detecting the security breach may trigger another vehicle to activate its alarm and that alarms may be triggered in all relevant vehicles in the network. Volvo further teaches that the alarms include blinking vehicle lights and honking vehicle horns. (Volvo, paras 0058-0059, 0061-0062, 0070-0072). Volvo expressly teaches that, in response to an intrusion, the alarms of vehicles 100 and 200 engage with honks and/or lights “to stress the trespassers,” and further teaches a neighborhood implementation in which a network of vehicles engages its alarms in response to an intrusion or physical attack. (Volvo, paras 0075-0077). Thus, Volvo teaches a collaborative deterrence strategy in which a plurality of vehicles collectively performs deterrence actions in response to detected suspicious activity.
Volvo further teaches controlling at least one of the group of vehicles to perform its assigned sub-task of the collaborative deterrence strategy. Volvo teaches triggering another vehicle 200 to activate its associated alarm and further teaches triggering vehicle 100 and at least one other vehicle 200 to activate their respective alarms upon determining the likelihood of a security breach. (Volvo, paras 0059, 0062, 0071-0072).
Volvo, however, does not expressly teach assigning sub-tasks of the collaborative deterrence strategy to a group of vehicles based on respective resource and capability profiles of the group of vehicles.
Cui teaches this limitation. Cui teaches collaborative task performance by a plurality of autonomous vehicles wherein autonomous vehicles collaborate based on their respective capabilities and resources. Cui teaches maintaining a fleet database containing capability information for respective autonomous vehicles, including maneuvering capabilities, payload/lift capabilities, sensor and recording capabilities, lighting capabilities, visual projection capabilities, and sound broadcast capabilities. (Cui, paras 0012, 0014-0015, 0036-0037).
Cui further teaches that an autonomous vehicle that cannot perform an entire task may identify another autonomous vehicle having capabilities matching requirements that the first vehicle cannot fulfill and collaborate with that vehicle. (Cui, paras 0018, 0020, 0050-0051). Cui expressly teaches that a collaborating autonomous vehicle may perform only a part of a portion of the task while one or more other autonomous vehicles perform other parts of that portion. (Cui, para 0054).
Cui further teaches selecting a collaborating vehicle based on the vehicle being capable of performing the particular portion of the task, including selecting the vehicle that is most capable of performing that portion, and thereafter providing the selected vehicle with specific instructions for performing its portion of the task. (Cui, paras 0055-0057). Cui additionally teaches authorizing a second autonomous vehicle to perform a portion of a task based upon capability information and verifying that the second autonomous vehicle has capabilities commensurate with the portion of the task it intends to perform. (Cui, paras 0065, 0067-0069). Thus, Cui teaches assigning different portions or sub-tasks of a collaborative task among a group of vehicles based on the respective resource and capability profiles of the vehicles.
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify Volvo's collaborative multi-vehicle security and deterrence system according to Cui's teaching of assigning portions of a collaborative task to respective vehicles based on their available resources and capabilities. Volvo already teaches coordinating multiple vehicles to respond to a detected security breach, while Cui teaches a known technique for coordinating multiple vehicles by determining the capabilities of the participating vehicles and assigning respective portions of a collaborative task to vehicles having capabilities suited to those portions. One of ordinary skill would have been motivated to apply Cui's capability-based task allocation to Volvo's network of vehicles so that different deterrence functions are performed by vehicles possessing resources and capabilities suited to those functions, thereby efficiently utilizing the heterogeneous capabilities available among the cooperating vehicles and providing an effective collaborative response to the detected security breach. Such a modification would have amounted to the predictable use of Cui's known collaborative vehicle task-allocation technique to improve Volvo's known collaborative vehicle security system.
Regarding claim 2 and 15, Cui further teaches wherein the assigning is based on at least one of: differences in sensor resources across the group of vehicles by teaching that different autonomous vehicles possess different sensor capabilities and that collaborative task assignments are made according to those differences. In particular, Cui teaches an example in which AV1 possesses the capabilities required for a task except for an infrared camera, while AV3 possesses the required camera capability but lacks another capability necessary for the task. Cui teaches that neither vehicle can perform the task alone, but that the vehicles may collaborate to collectively satisfy the task requirements. Cui further teaches identifying other vehicles having capabilities matching requirements that the first vehicle cannot fulfill. (Cui, paras 0018, 0020, 0051).
Cui further teaches differences in audio-visual output capabilities across the group of vehicles. Cui teaches maintaining respective vehicle capability profiles identifying, among other capabilities, lighting capabilities, visual projection capabilities, and sound broadcast capabilities. Cui further teaches corresponding task requirements including lighting, projector, and loudspeaker requirements, and teaches assigning or selecting vehicles having capabilities commensurate with the requirements of the portion of the task to be performed. (Cui, paras 0014-0015, 0036-0037, 0064-0069).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Cui's teaching of assigning portions of a collaborative task according to differences in the sensor and audio-visual capabilities of participating vehicles to Volvo's collaborative multi-vehicle deterrence system. Such a modification would allow the respective deterrence sub-tasks to be performed by vehicles possessing resources suited to those particular sub-tasks, thereby more effectively utilizing the differing capabilities available among Volvo's networked vehicles.
Regarding claim 4 and 17, Cui teaches determining the first vehicle has superior audio output capabilities to the second vehicle by teaching that respective autonomous vehicles may have different sound broadcast capabilities and that collaborating vehicles are selected based on capabilities matching task requirements. Cui further identifies loudspeaker capability as a task requirement. (Cui, paras 0014-0015, 0020, 0036-0037, 0051, 0064-0069).
Volvo teaches assigning the first vehicle to output an audio-based deterrence action by teaching activation of vehicle alarms including honking the vehicle horn and further teaching use of honks to stress trespassers in response to a security breach. (Volvo, paras 0058-0059, 0075-0077).
Volvo further teaches assigning the second vehicle to perform a non-audio output-related sub-task of the collaborative deterrence strategy by teaching activation of vehicle lights as a deterrence action, including blinking vehicle lights and use of lights to stress trespassers. (Volvo, paras 0058, 0075-0077).
It would have been obvious to one of ordinary skill in the art to apply Cui’s capability-based task allocation to Volvo’s collaborative deterrence system so that an audio deterrence function is assigned to a vehicle having the stronger audio-output capability, while a non-audio deterrence function is assigned to another vehicle. This would predictably match each deterrence task with a vehicle having resources suited to performing that task.
Regarding claim 12, Volvo teaches a system comprising: one or more processors; and memory storing machine-readable instructions that, when executed by the one or more processors, cause the system to perform vehicle-security operations. Volvo expressly teaches a vehicle system including a CPU and memory storing instructions for carrying out its disclosed method. (Volvo, paras 0063-0072).
Volvo teaches responsive to detecting suspicious activity being perpetrated by an individual in relation to vehicles, determine a collaborative strategy to deter the suspicious activity by teaching detection of security breaches, including intrusion and physical attack, and causing multiple networked vehicles to activate alarms including honks and lights to stress trespassers. (Volvo, paras 0058-0062, 0075-0078).
Volvo further teaches control at least one of the group of vehicles to perform its assigned sub-task of the collaborative deterrence strategy by triggering another vehicle in the network to activate its associated alarm in response to the detected security breach. (Volvo, paras 0059, 0062, 0071-0072).
Volvo does not expressly teach assign sub-tasks of the collaborative deterrence strategy to a group of the vehicles based on at least one of: resource and capability profiles of the group of vehicles.
Cui teaches maintaining respective capability profiles for autonomous vehicles, including maneuvering, sensor/recording, lighting, visual projection, and sound-broadcast capabilities, and assigning portions of a collaborative task to vehicles according to capabilities matching the requirements of those portions. (Cui, paras 0014-0015, 0018, 0020, 0036-0037, 0051, 0054-0057, 0065-0069).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Cui’s capability-based collaborative task allocation to Volvo’s multi-vehicle deterrence system so that deterrence sub-tasks are assigned to vehicles according to their respective resources and capabilities. This would predictably match each deterrence function with a vehicle suited to perform that function.
Regarding claim 20, Volvo teaches responsive detecting suspicious activity being perpetrated by an individual in relation to vehicles, determining a collaborative strategy to deter the suspicious activity by teaching detection of a potential security breach associated with vehicles and, responsive thereto, coordinating multiple networked vehicles to activate alarms including horn and light outputs to stress or deter trespassers. (Volvo, paras 0058–0062, 0070–0077).
Volvo further teaches controlling at least one of the group of vehicles to perform its assigned sub-task of the collaborative deterrence strategy by teaching that a security event detected by one vehicle may cause another vehicle in the network to activate an alarm or other deterrence output. (Volvo, paras 0059, 0062, 0071–0077).
Volvo does not expressly teach assigning sub-tasks of the collaborative deterrence strategy to a group of the vehicles based on at least one of: resource and capability profiles of the group of vehicles; or positional relationships between the individual and respective vehicles of the group of vehicles.
Cui teaches the claimed alternative of resource and capability profiles of the group of vehicles by teaching respective autonomous-vehicle capability profiles including sensor/recording capabilities, maneuvering capabilities, lighting, visual projection, and sound-broadcast capabilities, and assigning portions of a collaborative task to respective vehicles according to whether their capabilities satisfy the requirements of the task portions. (Cui, paras 0014–0015, 0018, 0020, 0036–0037, 0051, 0054–0057, 0064–0069).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Cui’s capability-based collaborative task allocation to Volvo’s multi-vehicle deterrence system so that deterrence sub-tasks are assigned to respective vehicles according to their available resources and capabilities. This would predictably match each deterrence function with a vehicle suited to perform that function.
Claim 3 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Björkengren et al. (US 2020/0108796 A1, “Volvo”) in view of Cui et al. (US 2022/0171385) and further in view of Wright et al. (US 2020/0272509).
Regarding claim 3, Volvo in view of Cui teaches all of the limitations of claim 2. Wright further teaches wherein the group of vehicles comprises at least a first vehicle and a second vehicle and assigning the sub-tasks of the collaborative deterrence strategy to the first and second vehicles comprises: determining the first vehicle has superior processing resources to the second vehicle. Wright teaches an automotive distributed-processing system having heterogeneous computing resources, including CPUs, GPUs, DSPs, ASICs, and FPGAs, and teaches that the various processing modules have different computing capabilities. Wright further monitors available computing resources and computing-device speed and schedules tasks to particular computing resources based on the available resources and device speed. (Wright, paras 0002, 0004, 0011-0012, 0015-0018, 0040-0042, 0054-0055, 0060-0061).
Wright further teaches assigning the first vehicle to further analyze the activity of the one or more individuals in relation to the vehicles. Wright teaches allocating automotive computing tasks to computing resources according to the processing capabilities of those resources and expressly describes vehicle image/object analysis having different levels of computational demand. In particular, Wright teaches a first object-detection implementation providing a less accurate analysis while requiring fewer computing resources and a second implementation providing a more accurate analysis while requiring greater computing resources. (Wright, paras 0056-0059; Figs. 4A-4B). Volvo separately teaches analyzing sensor information relating to a potential security breach, including analyzing sensed parameters and camera captures relating to the security event. (Volvo, paras 0052-0057, 0080-0082).
Wright further teaches assigning the second vehicle to perform a less processor-intensive sub-task of the collaborative deterrence strategy. Wright teaches that different implementations of an application use different amounts of computing resources and expressly identifies an implementation that performs object analysis using fewer computing resources than a more computationally demanding implementation. Wright further teaches assigning particular jobs to particular computing nodes according to the computing resources available at those nodes, including assigning a job to a node having sufficient computing resources while allocating remaining resources to other applications. (Wright, paras 0039-0042, 0056-0061, 0071-0073).
Cui teaches applying this type of capability distinction across cooperating vehicles by identifying respective vehicle capabilities and assigning different portions of a collaborative task to vehicles capable of performing those portions. Cui expressly teaches that one vehicle may perform one portion of a collaborative task while another vehicle performs another portion according to the respective capabilities of the vehicles. (Cui, paras 0018, 0020, 0051, 0054-0057).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to further modify the collaborative vehicle system of Volvo and Cui according to Wright by considering the relative processing resources available to the collaborating vehicles when allocating the respective sub-tasks. Wright teaches that automotive computing resources possess heterogeneous processing capabilities and that computational tasks should be allocated according to available computing resources and the computational requirements of the tasks. One of ordinary skill would therefore have been motivated to assign a more processor-intensive analysis sub-task to a collaborating vehicle having superior processing resources while assigning a less processor-intensive deterrence sub-task to a vehicle having lesser processing resources, thereby efficiently utilizing the heterogeneous processing resources of the collaborating vehicles and avoiding assigning computational work to a vehicle lacking sufficient processing capacity.
Claims 5 and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Björkengren et al. (US 2020/0108796 A1, “Volvo”) in view of Cui et al. (US 2022/0171385), and further in view of Pisz et al. (US 2015/0077235).
Regarding claim 5 and 18, Volvo in view of Cui teaches all of the limitations of claim 2. Cui teaches determining the first vehicle has a superior visual display to the second vehicle by teaching that respective vehicles may have different visual projection capabilities and that collaborating vehicles are selected based on capabilities matching task requirements. (Cui, paras 0014-0015, 0020, 0036-0037, 0051, 0064-0069).
Pisz teaches assigning the first vehicle to display video of the one or more individuals on its superior visual display. Pisz teaches detecting a non-authenticated individual proximate to a vehicle and displaying an image of that individual on a vehicle window display as a warning that the individual is being recorded. Pisz further teaches that the vehicle camera may capture still photographs or video and that the recorded image may be displayed on the vehicle window image surface. (Pisz, paras 0009-0011, 0037-0042, 0080, 0090-0093; Figs. 19-20, 23).
Pisz expressly states that the vehicle system provides a visual warning of a potential vehicle break-in to deter such activity, and Figure 20 shows the detected individual displayed on the vehicle window together with the warning “YOU ARE BEING RECORDED.” (Pisz, paras 0037-0038, 0080; Fig. 20).
Volvo further teaches assigning the second vehicle to perform a non-visual output-related sub-task of the collaborative deterrence strategy by teaching an audio deterrence action comprising honking the vehicle horn to stress trespassers. (Volvo, paras 0058-0059, 0075-0077).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claim invention to apply Pisz’s vehicle-display deterrence technique within the collaborative system of Volvo and Cui so that a vehicle having superior visual-output capability displays the recorded individual, while another vehicle performs a non-visual deterrence action. This would predictably assign each deterrence function to a vehicle having resources suited to that function.
Claims 6 and 19 are rejected under 35 U.S.C. 103 as being unpatentable over Björkengren et al. (US 2020/0108796 A1, “Volvo”) in view of Cui et al. (US 2022/0171385), and further in view of Charette et al. (US 2017/0371339).
Regarding claim 6 and 19, Volvo in view of Cui teaches all of the limitations of claim 2. Cui teaches determining the first vehicle has superior autonomous driving capabilities to the second vehicle by teaching that collaborating autonomous vehicles may have different maneuvering capabilities and are selected based on capabilities matching the requirements of respective portions of a collaborative task. (Cui, paras 0014-0015, 0020, 0051, 0055-0057).
Charette teaches assigning the first vehicle to move autonomously to deter the suspicious activity. Charette teaches that when an approaching object is classified as a threat, countermeasures are activated to deter or address the threat, and when the vehicle includes autonomous driving capabilities, the vehicle can automatically drive away from the approaching threat. (Charette, paras 0010, 0026, 0035; claim 16).
Volvo teaches assigning the second vehicle to perform a non-autonomous driving-related sub-task of the collaborative deterrence strategy by teaching deterrence actions including honking the horn and flashing vehicle lights to stress trespassers. (Volvo, paras 0058-0059, 0075-0077).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filling date of the claim invention to apply Charette’s autonomous threat-response technique to the collaborative system of Volvo and Cui so that a vehicle having superior autonomous-driving capability performs the movement-based deterrence action, while another vehicle performs a non-driving deterrence action. This predictably matches each deterrence task with a vehicle having the capability suited to perform it.
Claim 7, 9-10 are rejected under 35 U.S.C. 103 as being unpatentable over Björkengren et al. (US 2020/0108796 A1, “Volvo”) in view of Cui et al. (US 2022/0171385), and further in view of Jayanthi et al. (US 2019/0035171).
Regarding claim 7, Volvo in view of Cui teaches all of the limitations of claim 1. Jayanthi teaches wherein the assigning is further based on positional relationships between the one or more individuals and respective vehicles of the group of vehicles by teaching a coordination server that communicates with a plurality of mobile devices associated with respective vehicles and assigns tasks according to the vehicles’ current locations relative to the location associated with the task. In particular, Jayanthi teaches assigning a task to a vehicle determined to be in immediate proximity to the task location and opportunistically assigning customer-specific tasks to a vehicle whose current location is in proximity to the location associated with the task. (Jayanthi, paras 0025, 0029, 0051, 0053, 0055, 0103).
Volvo teaches that the location of the detected individual/security event is associated with the vehicle-security response. Thus, applying Jayanthi’s proximity-based task-assignment technique to Volvo and Cui would result in assigning collaborative deterrence sub-tasks based additionally on the positions of the participating vehicles relative to the detected individual.
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Jayanthi’s location-based task assignment to the collaborative deterrence system of Volvo and Cui so that a deterrence sub-task is assigned to a vehicle positioned favorably relative to the suspicious individual. This would predictably permit a vehicle nearer to the suspicious activity to perform the corresponding deterrence action more effectively.
Regarding claim 9, Volvo further teaches responsive to detecting the suspicious activity being perpetrated by the one or more individuals in relation to the vehicles: determining a collaborative strategy to monitor the suspicious activity. Volvo teaches a network of multiple vehicles having sensors for monitoring their surroundings, including microphones, image sensors, radar, and lidar, and teaches that high-power sensors associated with the vehicle or another vehicle may be activated upon detection of a potential security event. Volvo further teaches continuously monitoring for acoustic security signals, periodically scanning for dynamic objects, activating cameras to more precisely identify a potential security breach, and analyzing captured images. (Volvo, paras 0030-0036, 0064-0068, 0078-0080).
Cui teaches assigning sub-tasks of the collaborative monitoring strategy to the group of vehicles based on the resource and capability profiles of the group of vehicles. Cui expressly teaches collaborative performance of a security-surveillance task and assigns portions of a task among autonomous vehicles according to respective capability information, including image-capture and sensor capabilities. (Cui, paras 0020, 0078; claims 7, 9, 12-13).
Jayanthi further teaches assigning tasks based on positional relationships between the one or more individuals and respective vehicles of the group of vehicles by teaching assignment of tasks among respective vehicle-associated devices according to their current locations and proximity to the location associated with the task. (Jayanthi, paras 0025, 0029, 0051, 0053, 0055).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Cui’s capability-based collaborative task allocation and Jayanthi’s proximity-based assignment technique to Volvo’s multi-vehicle security monitoring system so that monitoring sub-tasks are assigned to vehicles according to both their available monitoring capabilities and their positions relative to the suspicious activity. This would predictably assign each monitoring function to a vehicle suited and positioned to perform it effectively.
Regarding claim 10, Cui further teaches wherein assigning the sub-tasks of the collaborative monitoring strategy is based on at least one of: differences in video-recording resources and video-recording capabilities across the group of vehicles by teaching that autonomous vehicles have different capability profiles, including image-capture capabilities, and that portions of collaborative tasks are assigned to vehicles based on whether their respective capabilities satisfy the requirements of the task. Cui further expressly identifies imaging and security-surveillance tasks as collaborative vehicle tasks. (Cui, paras 0014-0015, 0020, 0051, 0055-0057; claim 7).
Volvo further teaches video/image monitoring in the security context by teaching high-power image sensors associated with the vehicle or another vehicle, wherein an image sensor captures images of the vehicle surroundings and may be triggered in a network of vehicles in response to a security-related event. (Volvo, paras 0030, 0035, 0040-0041, 0049; claims 1, 9-10).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Cui’s capability-based task allocation to Volvo’s collaborative monitoring system so that video-monitoring sub-tasks are assigned to vehicles having the video/image-recording resources suited to perform those tasks. This would predictably utilize the differing recording capabilities available among the cooperating vehicles.
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Björkengren et al. (US 2020/0108796 A1, “Volvo”) in view of Cui et al. (US 2022/0171385), and further in view of Laur et al. (US 2017/0057497).
Regarding claim 13, Volvo in view of Cui teaches all of the limitations of claim 12.
Laur teaches wherein the assigning based on the positional relationships between the individual and the respective vehicles is based on a detected location and attentional direction of the individual with respect to the respective vehicles. Laur teaches detecting a pedestrian proximate to a vehicle and determining a location of the pedestrian, including the pedestrian’s range and direction relative to the vehicle and transforming pedestrian location information into the coordinate reference frame of the host vehicle. (Laur, paras 0010–0012, 0026–0027).
Laur further teaches determining an attentional direction of the individual with respect to the respective vehicles by determining a gaze-direction of the pedestrian, which indicates where or in what direction the pedestrian is looking, including determining whether the pedestrian is looking directly at the host vehicle. Laur further uses the pedestrian’s gaze direction to determine the vehicle response. (Laur, paras 0016–0019; Fig. 2; claim 3).
Therefore, it would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to apply Laur’s pedestrian-location and gaze-direction determinations to the collaborative deterrence system of Volvo and Cui so that assignment of the deterrence sub-tasks further accounts for both the detected location and attentional direction of the individual relative to the participating vehicles. This would predictably permit an appropriate vehicle to perform the deterrence action based on which vehicle is spatially associated with and receiving the attention of the individual.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure.
Esson (US 2006/0103541) para 0022-0025
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/OMEED ALIZADA/Primary Examiner, Art Unit 2686
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